Skill UI

Process videos, audio, images, and documents on Transloadit’s cloud using 86+ robots to encode formats, generate thumbnails, resize/watermark, run OCR, speech-to-text, moderation, and chain multi-step pipelines for scalable media automation.

A comprehensive automation toolkit designed to manage the entire Vercel deployment lifecycle and associated infrastructure. Users can programmatically monitor, trigger, and manage deployments, configure custom domains and DNS records, manage environment variables across multiple targets, and oversee project settings and project listings. Essential for implementing robust CI/CD pipelines and managing cloud infrastructure.

This comprehensive toolkit automates critical Webflow operations, including managing CMS collections (create, update, delete), site publishing, page inspection, and asset uploads. By connecting via Rube MCP, it allows developers to programmatically interact with Webflow's backend, making it ideal for implementing automated content workflows, CI/CD pipelines, and large-scale content management systems.

A comprehensive guide to setting up and managing Continuous Integration and Continuous Deployment (CI/CD) pipelines within KubeSphere. This tool integrates with Jenkins, supports both graphical editing and Jenkinsfile-based workflows, and enables automated deployments across multi-cluster environments using ArgoCD for GitOps management. Ideal for managing the full software delivery lifecycle.

This skill guides the management of CI/CD pipelines within KubeSphere DevOps. It utilizes Kubernetes Custom Resources (CRs) to define, trigger, and monitor complex build workflows, seamlessly integrating with Jenkins concepts in a cloud-native manner. Use it for automating build, test, and deployment processes for applications running on Kubernetes.

This skill guides users on operating the FrontendIntegration resources and the associated frontend-forge extension using kubectl. It covers the full lifecycle management: creating FI from complete YAML, updating status, enabling/disabling, troubleshooting build output, and managing the extension's installation plan. Ideal for DevOps engineers responsible for robust CI/CD pipeline management.

This skill provides comprehensive integration with the Benchling cloud platform using the Python SDK and REST API. It allows users to programmatically manage critical life sciences data, including registry entities (DNA/RNA/proteins), inventory tracking, ELN entries, workflows, and querying the Data Warehouse. Ideal for automating complex lab data pipelines and syncing Benchling with external systems.

Biopython is a robust, comprehensive toolkit for computational molecular biology written in Python. It enables users to manipulate biological sequences (DNA, RNA, protein), parse standard formats (FASTA, GenBank, PDB, etc.), and programmatically access major bioinformatics databases like NCBI via Entrez. This skill is ideal for developing complex bioinformatics pipelines, including sequence alignment, structural analysis, and phylogenetic tree construction.

Datamol provides a simplified, Pythonic abstraction layer over RDKit, making complex molecular operations accessible for chemical data science. It supports core functionalities including SMILES parsing, structure standardization, calculation of molecular descriptors (e.g., LogP, MW), 3D conformer generation, and efficient parallel batch processing. It is ideal for streamlining molecular data handling in drug discovery and chemical research pipelines.

A comprehensive toolkit for developing and executing genomics pipelines on the DNAnexus cloud platform. It provides capabilities for app/applet building, managing large biomedical datasets (FASTQ, BAM, VCF), orchestrating complex workflows, and interacting programmatically using the dxpy Python SDK.

A lightweight Python library designed for reading, parsing, and writing Flow Cytometry Standard (FCS) files. It extracts event data as NumPy arrays, handles complex metadata, and supports multiple FCS versions (2.0-3.1). Ideal for data preprocessing, building cytometry pipelines, and inspecting experimental results.

Gtars is a high-performance toolkit written in Rust with Python bindings, designed for comprehensive analysis of genomic interval data. It provides specialized modules for overlap detection, generating coverage tracks (WIG/BigWig), tokenization for Machine Learning models, and detailed fragment analysis in single-cell genomics. Use it for robust bioinformatics pipelines and computational genomics research.